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--- |
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license: mit |
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base_model: indolem/indobert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: apwic/indobert-base-uncased-finetuned-nergrit |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# apwic/indobert-base-uncased-finetuned-nergrit |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1176 |
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- Validation Loss: 0.1784 |
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- Train Accuracy: 0.9483 |
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- Epoch: 15 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2352, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 0.4507 | 0.1933 | 0.9437 | 0 | |
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| 0.1708 | 0.1795 | 0.9471 | 1 | |
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| 0.1295 | 0.1784 | 0.9483 | 2 | |
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| 0.1169 | 0.1784 | 0.9483 | 3 | |
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| 0.1172 | 0.1784 | 0.9483 | 4 | |
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| 0.1180 | 0.1784 | 0.9483 | 5 | |
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| 0.1176 | 0.1784 | 0.9483 | 6 | |
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| 0.1172 | 0.1784 | 0.9483 | 7 | |
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| 0.1168 | 0.1784 | 0.9483 | 8 | |
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| 0.1174 | 0.1784 | 0.9483 | 9 | |
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| 0.1174 | 0.1784 | 0.9483 | 10 | |
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| 0.1178 | 0.1784 | 0.9483 | 11 | |
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| 0.1175 | 0.1784 | 0.9483 | 12 | |
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| 0.1175 | 0.1784 | 0.9483 | 13 | |
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| 0.1179 | 0.1784 | 0.9483 | 14 | |
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| 0.1176 | 0.1784 | 0.9483 | 15 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.13.3 |
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